class_docstr: Base class for implementing dataset builders. See more information
  on top. Child class needs to implement ``build`` and ``load``.
  
  Args:
      dataset_name (str): Name of the dataset passed from child.
code: def setup(
      self,
      stage: Optional[str] = None,
      config: Optional[DictConfig] = None,
  ):
      if config is None:
          config = self.config
  
      self.config = config
      self.train_dataset = self.load_dataset(config, "train")
      self.val_dataset = self.load_dataset(config, "val")
      self.test_dataset = self.load_dataset(config, "test")
  
imports: import uuid
  from typing import Optional
  import pytorch_lightning
  from mmf.utils.build import build_dataloader_and_sampler
  from mmf.utils.logger import log_class_usage
  from omegaconf import DictConfig
  from torch.utils.data import Dataset
label_desc: Use image node_id 5 for calling the BaseDatasetBuilder obj's underlying member method code with example usage: obj.setup(stage, config) without return types